Codebook Homomorphic Encryption for Compressed Private Computing

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Solution Overview

Problem

Existing data compression techniques do not support privacy-preserving computations on compressed data, and fully homomorphic encryption schemes suffer from significant ciphertext expansion and computational overhead, limiting their practicality in real-world applications.

Innovation Solution

A codebook-based homomorphic encryption system that combines data compression and homomorphic encryption by quantizing data, generating an optimized codebook, and performing operations on compressed codewords using a homomorphic encryption scheme like the Paillier cryptosystem, with error correction techniques to maintain accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If fully homomorphic encryption schemes are used to enable computations on encrypted data, then privacy preservation is improved, but ciphertext expansion and computational overhead increase significantly

Engineering Contradiction:

Improveprivacy preservationVSAvoidciphertext expansion and computational overhead

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the encryption process by introducing an intermediate compression stage between data generation and homomorphic encryption. Data is first compressed using traditional compression algorithms, then encrypted. This segmentation allows the system to benefit from both compression efficiency and encryption security while avoiding the full overhead of compressing encrypted data directly.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies preliminary compression action before encryption. By compressing the plaintext data first and then encrypting the compressed result, the system reduces the amount of data that needs to be encrypted and processed homomorphically, thereby reducing ciphertext expansion and computational overhead while maintaining privacy preservation.

Inventive Principle:

Principle #10Preliminary action

2Productivity

If traditional data compression techniques are used to reduce storage and transmission costs, then compression efficiency is improved, but support for privacy-preserving computations on compressed data is lost

Engineering Contradiction:

Improvecompression efficiencyVSAvoidprivacy-preserving computation capability

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent introduces compressed plaintext data as an intermediary representation between original data and encrypted data. This intermediary form enables efficient storage and transmission while the subsequent homomorphic encryption of this compressed form preserves the ability to perform privacy-preserving computations on the compressed data itself.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent creates a multi-functional system where compressed data serves dual purposes: it provides efficient storage and transmission (traditional compression function) and simultaneously serves as input for homomorphic encryption to enable privacy-preserving computations (cryptographic function). This universality resolves the contradiction by making the compressed data form serve both efficiency and security needs.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Quantity of substance

If data is compressed before encryption to reduce ciphertext size, then storage and transmission costs are reduced, but computational accuracy may deteriorate due to compression artifacts

Engineering Contradiction:

Improveciphertext sizeVSAvoidcomputational accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent applies partial compression action, using traditional compression algorithms to reduce data size while accepting some compression artifacts. The key insight is that the compressed data is then encrypted and processed homomorphically, which actually helps mitigate accuracy loss by maintaining precision in the encrypted domain, thus achieving a balance between size reduction and accuracy preservation.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12574207B2Codebook-based homomorphic encryption for efficient and privacy-preserving data processing

Publication Date: 2026.03.10 ATOM BEAM TECHNOLOGIES INC

AI summary

The codebook-based homomorphic compression system is a novel approach that combines data compression and homomorphic encryption to enable efficient and secure computation on compressed data. It involves quantizing the input data, generating an optimized codebook using techniques like Huffman coding or deep learning, and compressing the data by replacing each value with its corresponding codeword. The compressed data is then encrypted using a homomorphic encryption scheme, such as the Paillier cryptosystem, allowing computations to be performed directly on the encrypted compressed data without decryption. Homomorphic properties of the encryption scheme enable operations like addition and multiplication on the ciphertexts, while preserving the confidentiality of the underlying data. The system also incorporates error correction techniques to mitigate the impact of quantization and encryption on the accuracy of the computations. This approach combines the benefits of data compression and homomorphic encryption, enabling efficient storage, transmission, and secure computation on compressed data.